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How Many Credits Should an Undergraduate Take?

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Abstract

Low completion rates and increased time to degree at U.S. colleges are a widespread concern for policymakers and academic leaders. Many ‘full time’ undergraduates currently enroll at 12 credits per semester despite the fact that a bachelor’s degree cannot be completed within 4 years at that credit-load. The academic momentum perspective holds that if, at the beginning of their first year in college, undergraduates attempted more course credits per semester, then overall graduation rates could rise. Using nationally-representative data and propensity-score matching methods to reduce selection bias, we find that academically and socially similar students who initially attempt 15 rather than 12 credits do graduate at significantly higher rates within 6 years of initial enrollment. We also find that students who increase their credit load from below fifteen to fifteen or more credits in their second semester are more likely to complete a degree within 6 years than similar students who stay below this threshold. Our evidence suggests that stressing a norm that full time enrollment should be 15 credits per semester would improve graduation rates for most kinds of students. However, an important caveat is that those undergraduates whose paid work exceeds 30 h per week do not appear to benefit from taking a higher course load.

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Notes

  1. The authors note, however, that they find no evidence that taking a high credit load lowers the odds of completion either—the finding is null. We suspect that the commonsense suspicion that past a certain point taking additional credits is likely to no longer be beneficial and possibly even injurious has merit. The question is not whether this point exists but where it is. Our hypothesis is that for most students, fifteen credits per semester does not push them beyond this saturation point.

  2. Sample sizes are rounded to the nearest 10 in accordance with NCES data restrictions.

  3. Selection on unobserved characteristics does not threaten the validity of estimates from an IV estimator. But IV requires that a valid and effective instrument (one with substantial effect on assignment to treatment) be identified, and we did not to identify such an instrument.

  4. We tested the robustness of our findings to changes in bandwidth; estimates were quite stable when bandwidths were between 0.01 and 0.15. Results at different bandwidths are presented in the Appendix in Tables 11, 12, and 13.

  5. We prefer this simulation-based method because it permits the researcher to adjust two parameters simulateously: the effect of the confounder on selection as well as the effect of the confounder on the outcome. Both Rosenbaum bounds and Mantel–Haenszel bounds only permit adjustment of the hypothetical effect of the confounder on selection, leaving its effect on the outcome obscure.

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Acknowledgments

This research was funded through a grant from the Bill and Melinda Gates foundation.

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Authors and Affiliations

  1. The Graduate Center, The City University of New York (CUNY), New York, USA

    Paul Attewell

  2. Wisconsin HOPE Lab, University of Wisconsin-Madison, Madison, WI, USA

    David Monaghan

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  1. Paul Attewell
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  2. David Monaghan
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Correspondence to David Monaghan.

Appendix

Appendix

See Tables 8, 9, 10, 11, 12, and 13. See Figs. 4 and 5.

Table 8 Balance statistics for propensity score matching analysis in Table 3, all students (cols 2–4)
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Table 9 Balance statistics for propensity score matching analysis in Table 3, community college students (cols 5–7)
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Table 10 Balance statistics for propensity score matching analysis in Table 3, 4-year college students (cols 8–10)
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Table 11 Robustness of treatment effects to changes in bandwidth parameter, all students (N = 6730)
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Table 12 Robustness of treatment effects to changes in bandwidth parameter, community college students (N = 1670)
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Table 13 Robustness of treatment effects to changes in bandwidth parameter, 4-year college students (N = 5070)
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Fig. 4
figure 4

Distrubution of propentisity score: community college students

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Fig. 5
figure 5

Distribution of propentisity score: four year students

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Attewell, P., Monaghan, D. How Many Credits Should an Undergraduate Take?. Res High Educ 57, 682–713 (2016). https://doi.org/10.1007/s11162-015-9401-z

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